Credit card fraud is a crime that has affected about ten percent of the American population, with a median fraudulent transaction value of 399 U.S. dollars. Globally, the total amount of transactions involved in credit card fraud adds up to about 5.5 billion U.S. dollars in 2012. The majority of credit card fraud is perpetrated by either using counterfeit cards (about 37%) and or lost/stolen cards (about 23%), which often occur at a point of sale.
Existing technology attempts to alleviate the problem of correctly authorizing financial transactions by using computationally complex heuristics and expensive computer systems to determine if a transaction matches the profile or behavior of the authorized end-user. However, heuristics are complex, computationally expensive, data intensive, relatively slow algorithms and have success rates of varying degrees. Specifically, current heuristics and computational power fail to meet the needs of consumers because of, but not limited to, the following reasons: (a) end-users are incorrectly flagged as having made an unauthorized transaction; (b) fraudulent transactions are not flagged as having made an unauthorized transaction; (c) analysis of transactions is done asynchronously out of band so transactions are allowed to complete before fraud is detected; and (d) they don't have access to a user's real-time data.
Despite the prior attempts to improve financial transaction fraud protection, a need exists for a system and method for financial authorization (e.g., Credit Card transactions) based on third party data, such as social media data, to reduce the reliance on ineffective fraud detection heuristics and expensive computing power.